def __init__(self, input_width, state_width, learning_rate):
self.input_width = input_width
self.state_width = state_width
self.learning_rate = learning_rate
# 门的激活函数
self.gate_activator = SigmoidActivator()
# 输出的激活函数
self.output_activator = TanhActivator()
# 当前时刻初始化为t0
self.times = 0
# 各个时刻的单元状态向量c
self.c_list = self.init_state_vec()
# 各个时刻的输出向量h
self.h_list = self.init_state_vec()
# 各个时刻的遗忘门f
self.f_list = self.init_state_vec()
# 各个时刻的输入门i
self.i_list = self.init_state_vec()
# 各个时刻的输出门o
self.o_list = self.init_state_vec()
# 各个时刻的即时状态c~
self.ct_list = self.init_state_vec()
# 遗忘门权重矩阵Wfh, Wfx, 偏置项bf
self.Wfh, self.Wfx, self.bf = (self.init_weight_mat())
# 输入门权重矩阵Wfh, Wfx, 偏置项bf
self.Wih, self.Wix, self.bi = (self.init_weight_mat())
# 输出门权重矩阵Wfh, Wfx, 偏置项bf
self.Woh, self.Wox, self.bo = (self.init_weight_mat())
# 单元状态权重矩阵Wfh, Wfx, 偏置项bf
self.Wch, self.Wcx, self.bc = (self.init_weight_mat())
def __init__(self, input_width, state_width, learning_rate):
self.input_width = input_width
self.state_width = state_width
self.learning_rate = learning_rate
self.gate_activator = SigmoidActivator()
self.output_activator = TanhActivator()
self.times = 0
self.c_list = self.init_state_vec()
self.h_list = self.init_state_vec()
self.f_list = self.init_state_vec()
self.i_list = self.init_state_vec()
self.o_list = self.init_state_vec()
self.ct_list = self.init_state_vec()
self.Wfh, self.Wfx, self.bf = (self.init_weight_mat())
self.Wih, self.Wix, self.bi = (self.init_weight_mat())
self.Woh, self.Wox, self.bo = (self.init_weight_mat())
self.Wch, self.Wcx, self.bc = (self.init_weight_mat())
def __init__(self, input_width, state_width, output_width,
learning_rate, penaltyL2, momentum):
self.input_width = input_width
self.state_width = state_width
self.output_width= output_width
self.learning_rate = learning_rate
self.penaltyL2 = penaltyL2
self.momentum = momentum
# 门的激活函数
self.gate_activator = SigmoidActivator()
# 输出的激活函数
self.output_activator = TanhActivator()
self.class_activator = SoftmaxActivator()
# 遗忘门权重矩阵Wfh, Wfx, 偏置项bf
self.Wfh, self.Wfx, self.bf, self.vWfh, self.vWfx, self.vbf =(self.init_weight_mat(0))
# 输入门权重矩阵Wfh, Wfx, 偏置项bf
self.Wih, self.Wix, self.bi, self.vWih, self.vWix, self.vbi =(self.init_weight_mat(0))
# 输出门权重矩阵Wfh, Wfx, 偏置项bf
self.Woh, self.Wox, self.bo, self.vWoh, self.vWox, self.vbo =(self.init_weight_mat(0))
# 单元状态权重矩阵Wfh, Wfx, 偏置项bf
self.Wch, self.Wcx, self.bc, self.vWch, self.vWcx, self.vbc =(self.init_weight_mat(0))
# 下一层权重Wy, 偏值by
self.Wy, self.by, self.vWy, self.vby =(self.init_weight_mat(1))